NiaOrg /
NiaPy
| @@ 87-99 (lines=13) @@ | ||
| 84 | """ |
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| 85 | return r"""None""" |
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| 86 | ||
| 87 | @staticmethod |
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| 88 | def typeParameters(): |
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| 89 | r"""Get dictionary with functions for checking values of parameters. |
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| 90 | ||
| 91 | Returns: |
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| 92 | Dict[str, Callable]: |
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| 93 | * delta (Callable[[Union[float, int], bool]): TODO |
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| 94 | """ |
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| 95 | return { |
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| 96 | 'delta': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 97 | 'T': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 98 | 'deltaT': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 99 | 'epsilon': lambda x: isinstance(x, float) and 0 < x < 1 |
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| 100 | } |
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| 101 | ||
| 102 | def setParameters(self, delta=0.5, T=2000, deltaT=0.8, coolingMethod=coolDelta, epsilon=1e-23, **ukwargs): |
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| @@ 156-162 (lines=7) @@ | ||
| 153 | """ |
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| 154 | return r"""Tan, Ying. "Firework Algorithm: A Novel Swarm Intelligence Optimization Method." (2015).""" |
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| 155 | ||
| 156 | @staticmethod |
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| 157 | def typeParameters(): return { |
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| 158 | 'N': lambda x: isinstance(x, int) and x > 0, |
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| 159 | 'm': lambda x: isinstance(x, int) and x > 0, |
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| 160 | 'a': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 161 | 'b': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 162 | 'epsilon': lambda x: isinstance(x, float) and 0 < x < 1 |
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| 163 | } |
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| 164 | ||
| 165 | def setParameters(self, N=40, m=40, a=1, b=2, A=40, epsilon=1e-31, **ukwargs): |
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